1. Technical Field
The invention generally relates to sound processing systems. More particularly, the invention relates to sound processing systems that adjust the sound output of the system based on the noise level in a listening area.
2. Related Art
Listening environments tend to have some amount of background or ambient noise. This noise is a challenge to sound-system designers, especially when the background or ambient noise is large or has a time-varying intensity. A sound system designer generally tries to play sound—such as music or voice—with enough volume that the sound being played can be heard over the background or ambient noise. The sound being played may come from a live or recorded audio source signal. This source signal may be a digital or analog electronic representation of the sound desired for a listening area. The source signal needs to be generated with enough strength that the resulting sound is audible over the background or ambient noise. Hence, sound-system designers may measure the background or ambient noise in a listening area and adjust the sound level of the source signal accordingly.
By determining the strength of the noise present, system designers can select an appropriate strength for the source signal, so that the sound being played has an adequate volume. This procedure may be done as part of a pre-performance calibration, such as a “sound check,” in which an audio system is empirically calibrated prior to use. A pre-performance calibration lets technicians select a strength for a source signal, so that the broadcast sound has an adequate volume for the acoustic properties and the noise in a particular listening area.
However, this solution may be insufficient when the noise in a listening area varies over time. The noise level can vary over time due to a variety of independently changing factors, such as the presence of people in the listening area, the foot traffic of people in the listening area, the number of the conversations of the people, the volume of the conversations, and the operation of machinery such as air handling units and the like. If the listening area is an outdoor location, there are additional factors that contribute to the time-varying noise, such as rain, wind, and nearby vehicular traffic.
Further, in some listening areas, some factors may be more pronounced than others, especially variable noise sources such as the operation of an air handling unit, vehicle noise, and the like. The variable noise sources can cycle between louder and softer noise levels during operation, increasing and decreasing the noise in the listening area. The noise measured during a pre-performance calibration might therefore not be a good representation of the ambient or background noise that occurs during a performance. Thus, although it may be helpful, a one-time calibration is not a full solution to the challenge of time-varying ambient noise.
A better approach is to use real-time measurements of the noise, with ongoing adjustments of the source signal's strength. The level of the source signal (which may be the source signal's amplitude or intensity or power) may then be increased in response to an increase in the noise and decreased in response to a decrease in the noise. This solution involves determining the level of ambient noise while the source signal is being played—for example, measuring the volume of crowd noise, weather, and machinery while a concert or other event is being performed—and adjusting the source signal's level as that ambient noise changes. This approach involves some additional challenges.
One challenge is to measure the sound level in the listening area and ascertain how much of that sound is noise and how much is from the source signal being projected into the listening area. A microphone may be used in the listening area to monitor the ambient sound, which is a combination of the desired sound and the ambient or background noise in the listening area. This combination of monitored sounds may be represented as a microphone signal, which may be understood as a combination of the source signal and the received noise. The microphone signal is a valuable tool for monitoring the listening area and providing feedback on the sounds being experienced in the listening area. Existing systems may fail to take account of the fact that by monitoring the listening area, a measurement microphone hears the extraneous noise as well as the desired sounds. Thus, these systems may essentially attenuate the sound being played in response to itself, which is not a desired solution.
Another technique for estimating the received noise is to subtract a scaled r.m.s. level of the source signal from the microphone signal. One of the main shortcomings of this approach is that it operates on the full audio band signal received at the microphone such that the r.m.s. value determined can be affected by the frequency response from loudspeakers to microphone. The potential error in the r.m.s. computation from this mechanism can exceed the level difference caused by extraneous noise sources in the room.
Another technique for estimating the received extraneous noise subtracts the source signal from the received microphone signal in the time domain. The technique measures the frequency response (or transfer function) from loudspeaker(s) to microphone and applies a complex frequency correction equalizer created in the digital domain as a Finite Impulse Response filter (FIR) and applies time delay to the source signal in an attempt to make both signal equivalent in the absence of extraneous noise. Because it is based on a time-domain comparison between the source signal and the microphone signal, this approach is largely insensitive to the frequency distribution of the noise and source signals. Further, the time delay for a signal to go from the source, such as a speaker or system of speakers, to the measurement microphone, is affected by factors such as the number and type of loudspeakers used in a sound system, placement of the loudspeakers, proximity of the loudspeakers to the measurement microphone, reverberant standing waves, and multiple signals arriving at the measurement microphone due to signal reflections, signal echoes, and multiple signals due to multiple loudspeakers. These delay factors result in a variety of delays known as time smear. Because of the variety of factors that contribute to these delays, a real-time time-domain approach may be of limited reliability for comparing a microphone signal to a source signal.
Yet another existing approach uses a fast Fourier transform to determine the level of noise present in a microphone signal. This approach is relatively complex, and involves a processing-intensive complete Fourier decomposition of the entire microphone signal.
Other approaches are limited to special applications, such as automotive sound systems, where special knowledge of the noise may be obtained from sources other than a microphone signal. For example, in the passenger compartment of an automobile, the main sources of extraneous noise include wind, tire noise, and engine noise. The level of these noise sources can be anticipated by inputs such as vehicle speed and engine speed, and the volume of the automobile's stereo system may be automatically adjusted. These approaches are not readily adaptable to more general situations, where the main indication of background or ambient noise is a microphone signal or some other input in which noise is combined with a desired sound.